Residual energy aware clustering algorithm for heterogeneous sensor networks

In clustered heterogeneous networks, some nodes are set as cluster heads, responsible to integrate the information from the intra-cluster members and send it to the sink node. Therefore cluster heads dissipate much more energy than other sensor nodes. And the stability of networks can be affected when the first node dies. We assume that nodes are assumed be equipped with different energy randomly, a clustering algorithm based on residual energy and multi-management for cluster heads is proposed. By adding a parameter into the probability of cluster head election, the proposed algorithm makes nodes with more initial energy and residual energy become cluster heads with large probability. It balances the energy consumption of network and prolongs the survival time of network. At the same time, in order to ensure the quality of network transmission, the strategy of multi-hop management is introduced in this algorithm. We show by simulation that the algorithm has a longer lifetime and more stable capacity of data transmission than LEACH, DEEC and SEP in the multi-level energy heterogeneous network.